The present invention relates generally to a data-centric reduction method, and more particularly, but not by way of limitation, to a system, method, and computer program product for reducing/compressing data generated from a plurality of sensors.
Conventionally, sensors and hardware counters implemented in modern computers generate massive data in terms of volume, velocity, and variability. The increasing amount of data transferred to the network results in overhead in a computing cluster such as implemented in high performance computing (HPC). This overhead may lead to unexpected noise that impacts running applications. However, the data contains redundancy. A data stream might report similar values for periods of time or different data streams might be strongly correlated, making all but one of them redundant. Therefore, the inventors have identified that there is a need in the art for reducing and/or compressing data generated from the plurality of sensors.